DocumentCode
3106185
Title
New Event Detect Based on LDA and Correlation of Subject Terms
Author
Li, Wei ; Huang, Ying
Author_Institution
Sch. of Inf. Eng., Jiangxi Univ. of Sci. & Technol., Ganzhou, China
fYear
2011
fDate
16-18 Aug. 2011
Firstpage
1
Lastpage
4
Abstract
Nowadays, topic detection and tracking (TDT) has been widely used. As one research tasks for TDT, new event detection can provide prior knowledge to TDT, so it has great theoretical research significance in the field of TDT. Because LDA model cannot automatically identify new events, and the number of LDA topic had been determined by the artificial, or by repeated experiments, it has low efficiency . Here presented a new method, which considering the correlation of subject terms and report time, it can dynamically adaptive updated topics, then detect the new event. This method can adaptive dynamic upload the number of topics, then determinate reasonable theme number. Experiment results demonstrate that this method has some ad-vantages, increased the sensitivity of new events detection.
Keywords
text analysis; LDA; new event detection; report time; subject terms correlation; topic detection; topic tracking; Computational modeling; Correlation; Event detection; Markov processes; Polynomials; Presses; Research and development;
fLanguage
English
Publisher
ieee
Conference_Titel
Internet Technology and Applications (iTAP), 2011 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-7253-6
Type
conf
DOI
10.1109/ITAP.2011.6006301
Filename
6006301
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